Mapping data to and from Excel files in Altova MapForce

MapForce ETL Features:

  • Map data to and from all popular databases
  • Map XML, flat files, EDI, Excel, XBRL, & Web services
  • Data processing functions convert data on the fly
  • Process data from/into multiple files
  • Direct file input and output (data streaming)
  • ETL automation through scripting or royalty-free code generation
  • Automated execution of ETL data mappings via FlowForce Server and MapForce Server

Download Trial

Enterprise ETL

ETL (Extract-Transform-Load) tools provide a mechanism for extracting data from external sources, transforming it to a normalized data format, and then loading it into an end target or repository. ETL is traditionally discussed in relation to data warehousing, but the process can also be a great asset when implemented for legacy data integration and other common business needs.

With support for prevalent enterprise data formats (XML, databases, flat files, EDI, etc.), MapForce is an extremely effective, lightweight, and scalable tool for ETL. MapForce offers a straightforward, visual user interface that lets you easily load any supported mapping structures and then use drag and drop functionality to connect nodes and add data processing functions and filters, or use the visual function builder for more complex ETL projects.

In addition to its visual interface, MapForce is also accessible through a command line interface and a flexible Java or COM-based API, providing an integrated automation layer to your ETL implementations.

ETL data mapping functions in Altova MapForce

ETL Data Processing

Most ETL implementations require the use of advanced data processing functions to manipulate data between source and target data formats. MapForce allows you to easily associate your ETL data structures using drag and drop functionality.

Advanced data processing filters and functions can be added via a built-in function library, and you can use the visual function builder to combine multiple inline and/or recursive operations in more complex ETL or data integration projects, and even save functions for use in other mapping projects.

MapForce also supports advanced ETL scenarios involving multiple input and output schemas, multiple source and/or target files, or advanced multi-pass data transformations.

Direct File Input and Output (Data Streaming)

Support for data streaming gives your ETL projects a huge performance boost with the ability to stream input from arbitrarily large XML, CSV, and FLF files and relational databases, and stream output to to equally large XML, CSV, and FLF files or insert it into a database.

This built-in functionality means that MapForce can easily process massive data sets and ETL projects, limited only by the amount of disk space available on your local machine or accessible on a network.

In order to activate this feature, simply select the BUILTIN icon from the toolbar in the MapForce design pane.

With support for bulk database insert as well as direct data streaming, MapForce Server is also ideally suited for execution of ETL data mappings.

Generating Program Code

MapForce supports ETL automation through generation of a complete royalty-free application in Java, C#, or C++ that performs the operations defined in your ETL mapping. The generated code can also be easily embedded into virtually any other application.